Diagnostic Criteria for Myalgic Encephalomyelitis/Chronic Fatigue Syndrome

CENTER FOR COMMUNITY RESEARCH

Diagnostic Criteria for Myalgic Encephalomyelitis/Chronic Fatigue

Syndrome

Leonard A. JasonCenter for Community Research

DePaul UniversityPresentation to the Institute of Medicine’s (IOM),

May 5, 2014


What is the Natural History of ME/CFS? What Are the Limits of Such Studies

Presently?• Very few studies in this area, particularly with best methodology

– prospective community-based samples• Jason, Porter et al. (2011a, 2011b) examined the course of

ME/CFS over a ten year period of time for a prospective, random, community-based, multi-ethnic sample

– There was relative stability over time on critical measures of disability, fatigue, support, optimism and coping over time

– The rate of ME/CFS remained approximately the same over the ten year period of time

– Post-exertional malaise best differentiated the ME/CFS group from the other groups (control, Idiopathic chronic fatigue, Medical/Psychiatric reasons for fatigue)

• This reaffirms the importance of this being a cardinal and critical symptom for ME/CFS.

– For unrefreshing sleep and impaired memory and concentration, 100% of the ME/CFS group had these symptoms

• Similar to post-exertional malaise, these results support the idea that unrefreshing sleep and impaired memory and concentration are core symptoms of ME/CFS


I was asked: Do Certain Symptoms in ME/CFS Appear to Cluster Together? More Precisely: Are Data Available on

What Symptoms Covary and How

• In order to accurately diagnose an illness or disease, it is important to have a reliable set of criteria for clinicians

• Otherwise, it is possible that disagreements about diagnostic decisions may arise because of diagnostic unreliability


Criterion Variance: Classification of Patients’ Symptoms

into Diagnostic Categories

• Criterion variance constitutes the largest source of diagnostic unreliability

• This typically occurs when an operationally explicit set of criteria is not being utilized in the process of diagnosing an illness

• Therefore, a case definition needs to specify the core, cardinal features of ME/CFS– In a recent systematic review, Brurberg, Fønhus, Larun,

Flottorp, and Malterud (2014) identified 20 case definitions– Problem is that different case definitions specify different

symptoms


Factor Analysis: Can be used to Determine which

Symptoms Covary

• Factor analysis identifies latent dimensions• Multiple factor analytic studies of

symptomatology have resulted in three to four symptom factors– Nisenbaum, Reyes, Mawle, & Reeves, 1998– Friedberg, Dechene, McKenzie, & Fontanetta,

2000 – Nisenbaum, Reyes, Unger, & Reeves, 2004– Arroll & Senior, 2009– Hickie et al., 2009


Brown and Jason’s (2014) Study Identified Three Factors

PainAutonomic

Neuro-endocrineImmune

Fatigue PEM

Neuro-cognitive


Interpretation of Brown et al. Study

• Two of the emergent factors were– Neurological/Cognitive Dysfunction– Post-Exertional Malaise – fit well with previous literature indicating that these are two of

the cardinal symptom clusters of ME/CFS • One factor was items from Neuroendocrine, Autonomic, &

Immune Dysfunction – more difficult to interpret as it incorporates many symptom

clusters• This suggests that there may be core, well-defined

symptom clusters such as cognitive impairment and post-exertional malaise– but also that there may be many other symptoms that are

experienced differently by patients


Are There Any Short Screen Tools That Have Been Validated for ME/CFS?

• Regardless of which case definition is used– it is critical to assess symptoms in a standardized

way to reduce reliability issues• such as the Wagner’s CFS Symptom Inventory

• By using a consistent set of items on a questionnaire or measure, as well as cut off points for defining whether a threshold has been met for symptom criteria– clinicians will be able to examine the same illness

constructs among all their participants or patients


Not Easy Determine Whether a Patient Meets a ME/CFS Case Definition

• Some investigators have found that over 90% of those with CFS Fukuda also meet the ME/CFS Canadian Clinical criteria (Fluge et al., 2011) whereas others have found the rates closer to 50% (Pheby et al. 2011) – This variability suggests that different

investigators might be using different scoring rules for diagnosing ME/CFS using the Canadian Clinical criteria


DePaul Symptom Questionnaire (DSQ) (Jason et al., 2010)

• Developed to provide a structured approach to gathering standardized information and to allow investigators to determine whether or not a patient meets the diagnostic criteria

• After completing the DSQ, algorithm determines if a patient meets case definitions including:– Myalgic Encephalomyelitis/Chronic Fatigue Syndrome

(ME/CFS; Carruthers et al., 2003)– Myalgic Encephalomyelitis (ME-ICC; Carruthers et al.,

2011– Chronic fatigue syndrome (CFS; Fukuda et al., 1994)


Psychometric Properties of the DSQ

• Good to excellent test-retest reliability (correlation coefficients for items on the DSQ)– Suggests that the overall instrument is a

reliable measure for examining symptoms and illness constructs within the patient community

• Brown & Jason (2014) indicates excellent internal consistency reliability


Dissemination• The DSQ is now being used in countries around the

world, including Canada, Mexico, Iran, England, Norway, and France

• Being used data collection efforts with the CFIDS Association Biobank, CDC multi-site study, Chronic Fatigue Initiative

• It is also being used in efforts to document specific vision-related abnormalities among patients – (Hutchinson, Maltby, Badham, & Jason, in press)

• A group of Iranian investigators are currently examining other psychometric properties of this instrument.

• Specialty Clinic in Vancouver using DSQ all new patients


Need Standardized Use of Measures

• Allow for a well-defined characterization of a patient’s illness

• Thus, clinicians will be able to better determine when examining those with ME, ME/CFS, and/or CFS

• Ultimately identify and work with more homogenous samples


DSQ Freely Available• The DePaul Symptom Questionnaire is

officially in the REDCap Shared Library– https://

redcap.vanderbilt.edu/consortium/library/search.php

• If your institution does not subscribe to REDCap, you can access the DSQ using this link– https

://redcap.is.depaul.edu/surveys/?s=tRxytSPVVw

https://redcap.vanderbilt.edu/consortium/library/search.php




https://redcap.is.depaul.edu/surveys/?s=tRxytSPVVw




In Terms of the Validated Questionnaires and Tools Used for the

Diagnosis of ME/CFS, How Do Patients with ME/CFS Compare

to Other “Sick" Controls? • ME/CFS is an illness as debilitating as Type

II diabetes mellitus, congestive heart failure, Multiple Sclerosis, end-stage renal disease – Anderson & Ferrans (1997); Buchwald,

Pearlman, Umali, Schmaling, & Katon (1996)


What Types of “Sick" Controls Have Been Used in the Past in Your or Others' Work?

What Work Is In Progress?

• One longitudinal study of youth after developing mono, they those who recovered and who did not were followed up at 6, 12, and 24 months. – Jason, Katz et al. (2013) found that days spent in bed since mono, along

with autonomic symptoms, were associated with post-infectious ME/CFS at 6 months

• Need include physically active and inactive healthy controls– Such studies could help us explore whether deconditioning is associated

with ME/CFS and the major outcome measures• Studies of exercise deconditioning using careful case-control

structures have not been able to explain ME/CFS on the basis of exercise deconditioning– Bazelmans, Bleijenberg, van der Meer, & Folgering, (2001); Bruno (2004);

van der Werf et al. (2000)


We Can Distinguish Between ME/CFS and Major Depressive Disorder

• Using Discriminant Function Analysis – 100% participants were classified correctly as

having ME/CFS or Depressive Disorder• Predictors

– Percent of time fatigue was reported– post-exertional malaise – unrefreshing sleep – confusion/disorientation – shortness of breath – severity self-reproach (BDI)

• Hawk, Jason, Torres-Harding (2006)


Jason et al. (1997) compared ME/CFS to MS and Lupus

• Early version of our scale differentiates patients with ME/CFS from those who are healthy– it is less likely to distinguish ME/CFS from other autoimmune

diseases (especially Lupus) • We will soon be recruiting larger samples of controls with MS

and Lupus, to see how they differ from those with ME/CFS using the DSQ

• We recommend a two-stage research design with – 1) a screening instrument with good sensitivity– 2) medical assessments of ME/CFS positives from stage 1 to deal

with the specificity problem


Extreme Care with Low Prevalence Illnesses

• Based on epidemiological evidence, in a sample of 100,000, there would be approximately 420 cases of ME/CFS

• According to Bayes' theorem – If a case definition had a 95% rate of sensitivity

and 95% specificity • would identify 399 of the 420 ME/CFS cases • Identify 4,979 individuals who did not have ME/CFS

but were identified as having it


Need Define What Counts as a Symptom

• Many questionnaires have measured severity but not frequency, and both need to be considered – Some symptoms are very severe, but if they

occur rarely, they are less likely to be considered a problem

• Also, many investigators consider mild severity as a cut off point, this decision can lead to including too many individuals into the case definition


DePaul Symptom Questionnaire:Frequency and Severity scales for each

symptom

0 1 2 3 4Scale:

Frequency: None of the time

A little of the time

About half of the time

Most of the time

All of the time

Severity: Symptom not present

Mild Moderate Severe Very severe


Frequency and Severity Scores of at least 1:


symptom

0 1 2 3 4Scale:




Most of the time

All of the time



100% 99% 99%96% 95% 95% 95%

98% 97%95%

94% 93%90%

96%

90%

86%

81% 81%

55%

65%

17%

7%

13%

19% 18%

49%

56%

37%

9%

51%

21%

44%

65%

39%

22%

6%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Percentage of CFS and Controls with Frequency and Severity Scores >=1 (Fukuda Criteria)

CFS Control

FatigueUnrefreshing

Sleep MusclePain

Head-aches Joint

Pain SoreThroat

TenderLymphNodes

Post-Exertional Malaise Memory & Concentration Problems

CFS Control


Misclassifications of Fukuda et al. (1994) CFS

33.7% of controls would meet Fukuda symptom requirements when including participants who report

frequency and severity scores of 1 or greater


Frequency and Severity Scores of at least 2:


symptom

0 1 2 3 4Scale:




Most of the time

All of the time



100% 99% 99%96% 95% 95% 95%

98% 97%95%

94% 93%90%

96%

90%

86%

81% 81%

55%

65%

17%

7%

13%

19% 18%

49%

56%

37%

9%

51%

21%

44%

65%

39%

22%

6%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%


CFS Control

96%

92%

86% 85%

69%

83% 83%

80%

73%

69%

66%68%

55%

73%

50%

64%

31%

44%

7%

16%

7%

2% 4% 5% 4%7%

2%

7%2% 5% 2%

10%7%

12%

1% 0%0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%


CFS Control

96%

92%

86% 85%

69%

83% 83%

80%

73%

69%

66%68%

55%

73%

50%

64%

31%

44%

7%

16%

7%

2% 4% 5% 4%7%

2%

7%2% 5% 2%

10%7%

12%

1% 0%0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%


CFS Control

Fatigue UnrefreshingSleep

MusclePain

Head-aches

JointPain

SoreThroat

TenderLymphNodes

Post-Exertional Malaise

Memory & Concentration Problems

FatigueUnrefreshing

Sleep MusclePain

Head-aches Joint

Pain SoreThroat

TenderLymphNodes

Post-Exertional Malaise Memory & Concentration Problems

CFS Control


Canadian Clinical ME/CFS (2003) criteria• Six or more months of fatigue• One symptom from each of the following

categories:– Post-Exertional Malaise– Sleep Dysfunction– Neurocognitive Impairments– Pain

• One symptom from two of the following categories:– Autonomic– Neuroendocrine– Immune

Sleep

PEM

Immune

Pain

AutonomicNeuroendocrine

Neurocognitive Immune, Neuroendocrine, & Autonomic symptoms have

lower prevalence

CFS Control

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Percentage of CFS and Controls with Frequency and Severity Scores >=2 (ME/CFS Symptoms)


Are There Any Data on How Patients of Different Ethnic/ Socio-Economic

Backgrounds Present? Are There Any Differences in Terms of

Their Presentation or Course of Illness?

• Few studies have examined these questions• Most research has been on Caucasian samples


Data from a Community-Based SampleJason, Taylor, Kennedy et al. (2001)

Symptoms experienced more severely by Minority participants

0

10

20

30

40

50

60

70

80

90

100

Sore throat PostexertionalMalaise

Headaches UnrefreshingSleep

Symptom

Severity Rating

MinorityCaucasian


Song, Jason, & Taylor(1999) Examined Sociodemographic

Differences

• Examined fatigue across African American, Caucasian, Latino and Asian American samples

• Latinos who were female, older, and of lower SES reported the highest relative severity of fatigue


Women Latinas Highest Fatigue

13.0013.10

13.44

12.90

12.3812.29

12.00

12.49

11.00

11.50

12.00

12.50

13.00

13.50

African Americans Caucasians Latinos Asian Americans

Racial/ethnic Groups

Mea

n Fa

tigue

FemaleMale


Among Latinos, Highest Fatigue Found Among Those Older and Lower SES

Latinos

12.23

12.80

13.22

12.91

11.6

11.8

12

12.2

12.4

12.6

12.8

13

13.2

13.4

Lower 50% Upper 50%

SES

Mea

n Fa

tigue

Younger 50%Older 50%

CENTER FOR COMMUNITY RESEARCHIn What Ways Are Community-Based Patients Different from

Those Recruited From Referral/ Specialty Centers?

• Issue not been well explored• Almost all studies of samples with patients

with ME/CFS have relied on referrals from physicians or health facilities


Jason, Plioplys et al. (2003) Compared Individuals Diagnosed with ME/CFS in a

Community-Based Sample to Patients with ME/CFS Who Were Recruited From

Tertiary-Care• Significantly more minorities in the Community versus

Tertiary samples • Within the ME/CFS-Community sample, 45% were white, 16% were

Black, 29% were Latino, and 10% were other• In the ME/CFS-Tertiary sample 93% were white, 5% were Black, 1%

were Latino and 1% were other• However, symptom criteria were significantly higher

among Tertiary as compared with the Community samples– memory and concentration problems, 96% vs 74%– sore throat, 76% vs 45%– tender lymph nodes, 65% vs 45%


Thoughts on the recent IOM with Gulf War Veterans

• In their review of factor-analytic studies, key question is whether the factor structure varies among compared populations

• As the report stated, that question is most appropriately posited as a formal statistical test– the probability of observing the differences between the

factor structures in the samples is estimated under the null hypothesis that the factor structures are the same in the two populations

• Unfortunately, almost all existing studies of factor-structure differences have failed to test the hypothesis directly– none have used structural equation models


Issues Needing Resolution• Reduce criterion variance by deciding which case

definition to use– Facilitate clinicians identify patients similar core symptoms

• Specify what instrument to use to measure the symptoms– Develop algorithms to help determine whether a patient meets

the case definition • Encourage research on ways to better operationalize key

elements of the case definition– Define Onset– Define Substantial Reductions– Define Lifelong fatigue– Define Time Period for Symptoms (6 months, 1 month, 1 week,

today)– Define Cutoffs for Frequency and Severity of Symptoms

0

10

20

30

40

50

60

70

80

90

100Chart Title

Chronic Bronchitis

Health significantly deteriorating

Illness Timeline:Level of Functioning over Time


Future Directions• In the critical decisions before your committee

– Collect and share data from patient groups, clinicians, NIH, CDC, IACFS/ME using quantitative and qualitative methods to inform an interactive and transparent process

– This will help secure the participation of key stakeholders• Learn from experiences of other diseases which

developed infrastructures to oversee refinements of case definition criteria– Recommend the development of an ongoing, flexible,

adaptive system that encourages clinical trials, research, incorporation of new findings into the case definition


References• Anderson, J. S., & Ferrans, C. E. (1997). The quality of life of persons with chronic fatigue syndrome. Journal of Nervous

Mental Disorders, 185, 359-367.• Brown, A., & Jason, L.A. (2014). Validating a measure of myalgic encephalomyelitis/chronic fatigue syndrome

symptomatology.. Manuscript under review.• Brurberg, K.G., Fønhus, M.S., Larun, L., Flottorp, S., & Malterud, K. (2014). (CFS/ME): a systematic review

syndrome/myalgic encephalomyelitis BMJ Open 2014 4:e003973• Buchwald, D., Pearlman, T., Umali, J., Schmaling, K., & Katon, W. (1996). Functional status in patients with chronic fatigue

syndrome, other fatiguing illnesses, and healthy individuals. American Journal of Medicine, 101, 364–370.• Hawk, C., Jason, L.A., & Torres-Harding, S. (2006). Differential diagnosis of chronic fatigue syndrome and major depressive

disorder. International Journal of Behavioral Medicine, 13, 244-251. • Hutchinson, C.V., Maltby, J., Badham, S.P., & Jason, L.A. (in press). Vision-related symptoms as a clinical feature of

Chronic Fatigue Syndrome/Myalgic Encephalomyelitis? Evidence from the DePaul Symptom Questionnaire. British Journal of Ophthalmology. doi:10.1136/bjophthalmol-2013-304439

• Jason, L. A., Brown, A., Evans, M., Sunnquist, M., & Newton, J. L. (2013). Contrasting chronic fatigue syndrome versus myalgic encephalomyelitis/chronic fatigue syndrome. Fatigue: Biomedicine, Health & Behavior, 1(3), 168-183.

• Jason, L.A., Katz, B.Z., Shiraishi, Y., Mears, C.J., Im, Y., Taylor, R.R. (2014). Predictors of post-infectious chronic fatigue syndrome in adolescents. Health Psychology and Behavioral Medicine: An Open Access Journal, 2, 41–51.

• Jason, L.A., Plioplys, A.V., Torres-Harding, S., & Corradi, K. (2003). Comparing symptoms of chronic fatigue syndrome in a community-based versus tertiary care sample. Journal of Health Psychology, 8, 459-464.

• Jason, L.A., Porter, N., Hunnell, J., Brown, A., Rademaker, A., & Richman, J.A. (2011a). A natural history study of chronic fatigue syndrome. Rehabilitation Psychology, 56, 32-42. PMCID: PMC3171164

• Jason, L.A., Porter, N., Hunnell, J., Rademaker, A., & Richman, J.A. (2011b). CFS prevalence and risk factors over time. Journal of Health Psychology, 16, 445-456. PMCID: PMC3166209

• Jason, L.A., Ropacki, M.T., Santoro, N.B., Richman, J.A., Heatherly, W., Taylor, R.R., Ferrari, J.R., Haney-Davis, T.M., Rademaker, A., Dupuis, J., Golding, J., Plioplys, A.V., & Plioplys, S. (1997). A screening instrument for Chronic Fatigue Syndrome: Reliability and validity. Journal of Chronic Fatigue Syndrome, 3, 39-59.

• Jason, L.A., Taylor, R.R., Kennedy, C.L., Harding, S.T., Song, S., Johnson, D., Chimata, R. (2001). Subtypes of chronic fatigue syndrome: A review of findings. Journal of Chronic Fatigue Syndrome, 8, 1-21

• Jason, L.A., Taylor, R.R., Kennedy, C.L., Jordan, K., Song, S., Johnson, D., & Torres, S. (2000). Chronic fatigue syndrome: Sociodemographic subtypes in a community-based sample. Evaluation and the Health Professions, 23, 243-263.

• Song, S., Jason, L.A., Taylor, R.R., Torres-Harding, S.R., Helgerson, J., & Witter, E. (2002). Fatigue severity among African Americans: Gender and age interactions. Journal of Black Psychology, 28, 53-65.

• Song, S., Jason, L.A., & Taylor, R.R. (1999). The relationship between ethnicity and fatigue in a community-based sample. Journal of Gender, Culture, and Health, 4, 255-268.

Diagnostic Criteria for Myalgic Encephalomyelitis/Chronic Fatigue Syndrome

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